Weronika van Vianen
Jersey City, New Jersey, United States
812 followers
500+ connections
About
I am a problem-solver who excels and thrives in a challenging and high-pace working…
Activity
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Gecko Robotics - changing the way we build, operate and maintain the physical world - around the world - from right here in Western PA. Thanks for…
Gecko Robotics - changing the way we build, operate and maintain the physical world - around the world - from right here in Western PA. Thanks for…
Liked by Weronika van Vianen
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PA Governor Josh Shapiro toured Gecko Robotics today and spoke with members of the press about his proposed budget which invests millions in dollars…
PA Governor Josh Shapiro toured Gecko Robotics today and spoke with members of the press about his proposed budget which invests millions in dollars…
Liked by Weronika van Vianen
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Had a great time talking ball at SLOAN and sharing some of my perspective on what makes working in the NFL so fun and challenging.
Had a great time talking ball at SLOAN and sharing some of my perspective on what makes working in the NFL so fun and challenging.
Liked by Weronika van Vianen
Experience
Education
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The University of Chicago Booth School of Business
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Activities and Societies: Dean's List each quarter starting with Autumn 2020.
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2016 class valedictorian
First undergraduate recipient of the Karl Menger Student Award for Exceptional Scholarship
Recipient of the College of Science Dean’s Undergraduate Research Stipend
Full tuition and board merit-based scholarship
Publications
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Numerical Methods for Estimating Correlation Coe cient of Trivariate Gaussians
SIAM Undergraduate Research Online (SIURO)
Given observed data, the fundamental task of statistical inference is to understand the underlying data-generating mechanism. This task usually entails several steps, including determining a good family of probability distributions that could have given rise to the observed data, and identifying the specific distribution from that family that best fits the data. The second step is usually called parameter estimation, where the parameters are what determines the specific distribution. In many…
Given observed data, the fundamental task of statistical inference is to understand the underlying data-generating mechanism. This task usually entails several steps, including determining a good family of probability distributions that could have given rise to the observed data, and identifying the specific distribution from that family that best fits the data. The second step is usually called parameter estimation, where the parameters are what determines the specific distribution. In many instances, however, estimating parameters of a statistical model poses a significant challenge for statistical inference. Currently, there are many standard optimization methods used for estimating parameters, including numerical approximations such as the Newton-Raphson method. However, they may fail to find a correct set of maximum values of the function and draw incorrect conclusions, since their performance depends on both the geometry of the function and location of the starting point for the approximation. An alternative approach, used in the field of algebraic statistics, involves numerical approximations of the roots of the critical equations by the method of numerical algebraic geometry. This method is used to find all critical points of a function, before choosing the maximum value(s). In this paper, we focus on estimating correlation coe cients for multivariate normal random vectors when the mean is known. The bivariate case was solved in 2000 by Small, Wang and Yang, who emphasize the problem of multiple critical points of the likelihood function. The goal of this paper is to consider the first generalization of their work to the trivariate case, and offer a computational study using both numerical approaches to find the global maximum value of the likelihood function.
Other authorsSee publication
Projects
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Optimization of Ebola Treatment Facility Placement in West Africa
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Over the course of a semester the group developed framework for determining and evaluating results of the SEIR disease model given data with over 10 thousand Ebola infected patients in Liberia. That required a design of an uncertainty quantification model for simulating the most optimal parameters of the SEIR model in the Mathematica programming language. In addition, we applied the CFLP algorithm to find the most optimal locations for the Ebola treatment places in Liberia.
The project…Over the course of a semester the group developed framework for determining and evaluating results of the SEIR disease model given data with over 10 thousand Ebola infected patients in Liberia. That required a design of an uncertainty quantification model for simulating the most optimal parameters of the SEIR model in the Mathematica programming language. In addition, we applied the CFLP algorithm to find the most optimal locations for the Ebola treatment places in Liberia.
The project resulted with a paper that was presented at PICMath Conference in Washington DC (Summer 2015)Other creators -
Honors & Awards
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Karl Menger Student Award
Illinois Institute of Technology
Awarded to one student in the Department of Applied Mathematics for excellence in scholarship.
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Winner of the Applied Mathematics Poster Competition
Illinois Institute of Technology
Poster presentation describing application of my research in "Numerical Methods for Estimating Correlation Coefficient of Trivariate Gaussians" to different scientific fields.
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College of Science Undergraduate Summer Research Stipends
Illinois Institue of Technology
Stipend allowed to conduct 10 weeks during the summer, which resulted in a publication (Numerical Methods for Estimating Correlation Coefficient of Trivariate Gaussians)
Languages
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English
Native or bilingual proficiency
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Polish
Native or bilingual proficiency
More activity by Weronika
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For 20 years the Princeton Consultants Optimization Practice, including Dinesh Maneyapanda and Robert Randall, has served the #aviation industry…
For 20 years the Princeton Consultants Optimization Practice, including Dinesh Maneyapanda and Robert Randall, has served the #aviation industry…
Liked by Weronika van Vianen
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Late-night sessions talking about AI, energy, space, building cities, and more with Sam Altman, Troy Demmer, Henrique Dubugras, John S. Kim, John…
Late-night sessions talking about AI, energy, space, building cities, and more with Sam Altman, Troy Demmer, Henrique Dubugras, John S. Kim, John…
Liked by Weronika van Vianen
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